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All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Emerging satellite observations for diurnal cycling of ecosystem processes

Diurnal cycling of plant carbon uptake and water use, and their responses to water and heat stresses, provide direct insight into assessing ecosystem productivity, agricultural production and management practices, carbon and water cycles, and feedbacks to the climate. Temperature, light, atmospheric water demand, soil moisture and leaf water potential vary over the course of the day, leading to diurnal variations in stomatal conductance, photosynthesis and transpiration. Earth observations from polar-orbiting satellites are incapable of studying these diurnal variations. Here, we review the emerging satellite observations that have the potential for studying how plant functioning and ecosystem processes vary over the course of the diurnal cycle. The recently launched ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) and Orbiting Carbon Observatory-3 (OCO-3) provide land surface temperature, evapotranspiration (ET), gross primary production (GPP) and solar-induced chlorophyll fluorescence data at different times of day. New generation operational geostationary satellites such as Himawari-8 and the GOES-R series can provide continuous, high-frequency data of land surface temperature, solar radiation, GPP and ET. Future satellite missions such as GeoCarb, TEMPO and Sentinel-4 are also planned to have diurnal sampling capability of solar-induced chlorophyll fluorescence. We explore the unprecedented opportunities for characterizing and understanding how GPP, ET and water use efficiency vary over the course of the day in response to temperature and water stresses, and management practices. We also envision that these emerging observations will revolutionize studies of plant functioning and ecosystem processes in the context of climate change and that these observations and findings can inform agricultural and forest management and lead to improvements in Earth system models and climate projections.

Plant functioning↗
DOE OSTI2022

Predictive models enhance feedstock quality of corn stover via air classification

Feedstock heterogeneity is a fundamental obstacle to cost-competitive biobased products. Agricultural products like corn stover have anatomical components that vary in their chemical composition, mechanical properties, structure, and response to chemical and biological treatments. A technique that can enrich streams in select anatomical fractions would allow a tailored deconstruction approach to increase overall process efficiency. Air classification can be leveraged for such refining, however, fundamental characterization and understanding of the particle properties that underly the physics of air classification are only modestly documented. Here, we determine fundamental particle properties including mass-to-area ratio, drag coefficient, and partition velocity that describe how anatomical tissues of corn stover behave during air classification. In this work, mass-to-area ratios of anatomical tissues vary by nearly two orders of magnitude from 2.3 mg/mm 2 for cob to 0.04 mg/mm 2 for leaf. Drag coefficients of longer, fibrous materials (i.e., rind, husk, and sheath) are shown to correlate with particle area (p-value < 0.001) whereas granular tissues (i.e., cob, pith, and leaf) correlate better with mass-to-area ratio (p-values < 0.001). When compared to experimental observations, a simulated two-stage air classification and size reduction scenario predicts the overall partitioning of anatomical tissues within 15% for pith, husk, rind, and cob tissues. The model predicts an air-classified fraction preferentially enriched in cob (purity = 20%), rind (purity = 74%), and pith (purity = 4.5%) with a mass yield of 47%. Empirical relations for these properties can be used to predict the partitioning of corn stover during air classification based on anatomical type and size.

09 BIOMASS FUELS↗
DOE OSTI2023

Using taxa-based approaches to delineate stream macroinvertebrate assemblage responses to stressor gradients in modified alluvial agroecosystems

Alluvial plain landscapes are some of the most agriculturally productive lands in the world but often have modified stream ecosystems due to cultivation history. This context requires consideration when establishing water quality management goals. We analyzed state water quality databases to demonstrate that Mississippi Alluvial Plain (MAP) ecoregion streams have elevated specific conductivity (SC) and nutrients and lower macroinvertebrate local and regional taxa pools compared to streams in other ecoregions, potentially reducing the efficacy of traditional biomonitoring approaches within the region. To overcome these challenges, we used threshold indicator taxa analysis (TITAN) to compare macroinvertebrate assemblage responses to water quality gradients among ecoregions in Mississippi. We identified individual taxa and assemblage-level responses to increasing water quality degradation in MAP streams. Observed responses occurred at higher concentrations for SC, total organic carbon (TOC) and total phosphorus (TP), but not total nitrogen (TN) relative to other ecoregions. These responses appeared to be driven by a large proportion of indicator taxa considered tolerant or unresponsive in other ecoregions, responding negatively to increasing water quality stressors in MAP streams. Our observed assemblage-level stressor responses to WQ gradients in MAP streams demonstrate shifting tolerance in highly altered ecosystems may require adjustments to recovery expectations but also provide useful measures for monitoring improvements in regional water quality. For example, our observed macroinvertebrate assemblage response to increasing TP identified a management goal similar to guidance based on distributional analysis of water quality data within the MAP ecoregion (0.11 vs 0.128 mg L –1 ) and thus provide some biological basis for previously identified nutrient goals for the region. Our approach can guide and monitor success of nutrient reduction efforts in MAP watersheds and other alluvial plain agroecosystems where reference conditions do not exist, and local and regional taxa pools are less diverse and may not support full recovery of ecological assemblages. While our results are promising, they should also be compared with more sensitive and less habitat-limited biological assemblages (e.g., algae or bacteria) to better understand complex ecological responses to best management practices designed to increase sustainability of high production agricultural regions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1989

Specification of parameters for development of a spatial database for drought monitoring and famine early warning in the African Sahel

Parameters were described for spatial database to facilitate drought monitoring and famine early warning in the African Sahel. The proposed system, referred to as the African Drought and Famine Information System (ADFIS) is ultimately recommended for implementation with the NASA/FEMA Spatial Analysis and Modeling System (SAMS), a GIS/Dymanic Modeling software package, currently under development. SAMS is derived from FEMA'S Integration Emergency Management Information System (IEMIS) and the Pacific Northwest Laborotory's/Engineering Topographic Laboratory's Airland Battlefield Environment (ALBE) GIS. SAMS is primarily intended for disaster planning and resource management applications with the developing countries. Sources of data for the system would include the Developing Economics Branch of the U.S. Dept. of Agriculture, the World Bank, Tulane University School of Public Health and Tropical Medicine's Famine Early Warning Systems (FEWS) Project, the USAID's Foreign Disaster Assistance Section, the World Resources Institute, the World Meterological Institute, the USGS, the UNFAO, UNICEF, and the United Nations Disaster Relief Organization (UNDRO). Satellite imagery would include decadal AVHRR imagery and Normalized Difference Vegetation Index (NDVI) values from 1981 to the present for the African continent and selected Landsat scenes for the Sudan pilot study. The system is initially conceived for the MicroVAX 2/GPX, running VMS. To facilitate comparative analysis, a global time-series database (1950 to 1987) is included for a basic set of 125 socio-economic variables per country per year. A more detailed database for the Sahelian countries includes soil type, water resources, agricultural production, agricultural import and export, food aid, and consumption. A pilot dataset for the Sudan with over 2,500 variables from the World Bank's ANDREX system, also includes epidemiological data on incidence of kwashiorkor, marasmus, other nutritional deficiencies, and synergistically-related infectious diseases.

Rochon, Gilbert L.↗
DOE OSTI2026

Data for Rewiring Yeast Metabolism for Producing 2,3-Butanediol and Two Downstream Applications: Techno-Economic Analysis and Life Cycle Assessment of Methyl Ethyl Ketone (MEK) and Agricultural Biostimulant Production

Rising concerns for sustainability and global climate change have driven the development of sustainable production pathways for biofuels and chemicals from lignocellulosic biomass via integrated biological and chemical processes. We constructed an engineered Saccharomyces cerevisiae capable of producing 2,3-butanediol (2,3-BDO) from glucose without accumulating ethanol and glycerol, which hinder downstream processing of 2,3-BDO, through extensive metabolic reprogramming. Specifically, we introduced heterologous 2,3-BDO biosynthetic enzymes and deleted the major isozymes of ethanol and glycerol biosynthetic enzymes. In addition, we introduced an NAD+ regenerating Pyruvate-Malate (PM) cycle and enhanced the NAD+ regenerating capability of the PM cycle to resolve the redox imbalance from the deletion of ethanol and glycerol production pathways. The resulting engineered yeast produced 109.9 g/L of 2,3-BDO with a productivity of 1.0 g/L/h and a yield of 0.36 g/g glucose in a fed-batch fermentation. We also conducted techno-economic analysis (TEA) and life cycle assessment (LCA) of the production of methyl ethyl ketone (MEK) through catalytic dehydration of 2,3-BDO. A TEA based on the experimental results indicated that the minimum product selling price (MPSP) was estimated to be $1.90/kg. Regarding cradle-to-grave LCA, 100-year global warming potential (GWP100) and fossil energy consumption (FEC) were found to be 0.37 kg CO2 eq/kg and 3.1 MJ/kg, respectively. These results demonstrated the feasibility of cost-competitive and sustainable bio-based MEK production via yeast fermentation. In addition, we explored the possibility of using the fermentation broth containing 2,3-BDO as a biostimulant inducing drought tolerance in plants. As a result, the yeast 2,3-BDO fermentation broth can induce drought tolerance in Arabidopsis thaliana without a complicated purification process.

Economics↗
DOE OSTI2023

Geographically Dependent Sustainability Indicators for Comparison of Conventional Vegetable Production to Controlled-Environment Agriculture

Many food system lifecycle analyses distill agricultural production and supply chain impacts into single-value sustainability metrics for various food categories. These studies provide an overview of the food supply system that highlight striking results such as the GHG impacts of meat production. The supply chain impacts of vegetable production occupy the middle ground; higher than average food loss and waste, lower than average overall energy use, etc. However, aggregated results obscure the sustainability implications of the location of food production, especially for vegetables. Moreover, the increasing instability of food production systems are not captured, as illustrated by a recent Washington Post article. According to a UC Merced study conducted for the state, California farmers left nearly 400,000 acres of agricultural land unplanted last year because of a lack of water. The result, the study found, was a direct economic cost to farmers of $1.1 billion and the loss of nearly 9,000 agricultural jobs. (The Washington Post, March 21, 2022.) Previous work quantified the food-energy-water nexus implications of transitioning vegetable production from large, centralized agricultural operations to smaller distributed production in controlled-environment farms (CEA). The importance of location-specific data is especially evident for water use. Water impacts of the food system are primarily local to the region where food is produced, water impacts vary significantly between locations, and water stress is a major concern in locations that currently host large agricultural operations. Location-specific data is needed to accurately assess the water impacts of transitioning to CEA. The location of farms in relation to consumers impacts transportation energy use, food loss and waste, and requirements for food processing (e.g., to reduce weight, preserve foods for long storage, and package foods to reduce damage and loss) Reducing transport is particularly relevant for agricultural products that could be grown in CEAs (fruits, vegetables, protein). Access to nutritious food is not evenly distributed in the population. Remote communities, communities in harsh environments, and economically-disadvantaged communities often have poor access to healthy foods. CEA is ideally suited to these environments. However, the energy and water use of CEA, while in many respects lower overall than conventional supply chains, are concentrated within communities and could have significant local impacts. This paper reports on development of sustainability metrics that seek to capture the tradeoffs between the current supply chain and a CEA supply chain for vegetables; focusing on the location-dependent implications of water use, the transition from largely fossil fuel based energy use to electricity, and the food access, resilience and wellbeing implications of urban versus rural food production.

controlled-environment agriculture↗
DOE OSTI2026

Agricultural crop production by county - mature-market medium scenario

This dataset contains data on agricultural crop production by county from 2022 to 2041. The agricultural crop in this dataset includes barley, biomass sorghum, corn, cotton, energy cane, eucalyptus, grain sorghum, hay, miscanthus, oats, pine, poplar, rice, soybean, switchgrass, wheat, and willow. The dataset was obtained from the database of the BT23 (Davis et al., 2024) for the mature-market medium scenario with biomass market prices from $30 to $130 per dry ton.

agricultural crop↗
NASA NTRS2014

Examining the Link Between Food Prices and Food Insecurity: a Multi-Level Analysis of Maize Price and Birthweight in Kenya

In developing countries where many poor people rely on rainfed, locally produced food for the majority of their caloric intake, shifts in climate and weather patterns can dramatically reduce agricultural productivity. The reduction in agricultural productivity reduces overall food availability and ultimately impacts food accessibility, putting millions of people at risk for malnutrition. In this project we focus on Kenya where roughly a third of households are food insecure. We examine the relationship of the price of maize and low birth weight to help quantify the impact of local food prices on one outcome of household food insecurity. Using spatially referenced data from recent Kenyan Demographic and Health Survey datasets, price data, livelihood information, and a remotely sensed-based measure of local growing season productivity, we develop a dataset linking pregnancies occurring from 2001 to 2008 to the spatially and temporally relevant maize price data. We construct several regression models to examine the impact of local maize prices and remotely sensed based estimates of crop production on infant birth weight - specifically low birth weight. The results of the models highlight the importance of including community crop production to evaluate maize price impacts on low birth weight outcomes. Also, because of the positive correlation between pre-pregnancy maize prices and birth weight, the results suggest that some households may benefit from high prices or that high prices may impact the number of conceptions. More generally, our work demonstrates that multilevel models that account for community-level variation are important for disentangling these complex relationships and can contribute to the discussion of how to design more effective food policies.

Low birth weight↗
NASA NTRS2013

The Effect of Agricultural Growing Season Change on Market Prices in Africa

Local agricultural production is a key element of food security in many agricultural countries in Africa. Climate change and variability is likely to adversely affect these countries, particularly as they affect the ability of smallholder farmers to raise enough food to feed themselves. Seasonality influences farmers' decisions about when to sow and harvest, and ultimately the success or failure of their crops. At a 2009 conference in the United Kingdom hosted by the Institute of Development Studies, Jennings and Magrath (2009) described farmer reports from East Asia, South Asia, Southern Africa, East Africa and Latin America. Farmers indicate significant changes in the timing of rainy seasons and the pattern of rains within seasons, including: More erratic rainfall, coming at unexpected times in and out of season; Extreme storms and unusually intense rainfall are punctuated by longer dry spells within the rainy season; Increasing uncertainty as to the start of rainy seasons in many areas; Short or transitional second rainy seasons are becoming stronger than normal or are disappearing altogether. These farmer perceptions of change are striking in that they are geographically widespread and are remarkably consistent across diverse regions (Jennings and Magrath, 2009). The impact of these changes on farmers with small plots and few resources is large. Farming is becoming riskier because of heat stress, lack of water, pests and diseases that interact with ongoing pressures on natural resources. Lack of predictability in the start and length of the growing season affects the ability of farmers to invest in appropriate fertilizer levels or improved, high yielding varieties. These changes occur at the same time as the demand for food is rising and is projected to continue to rise for the next fifty years (IAASTD, 2008). Long-term data records derived from satellite remote sensing can be used to verify these reports, providing necessary analysis and documentation required to plan effective adaptation strategies. Remote sensing data can also provide some understanding of the spatial extent of these changes and whether they are likely to continue. Given the agricultural nature of most economies on the African continent, agricultural production continues to be a critical determinant of both food security and economic growth (Funk and Brown, 2009). Crop phenological parameters, such as the start and end of the growing season, the total length of the growing season, and the rate of greening and senescence are important for planning crop management, crop diversification, and intensification. The World Food Summit of 1996 defined food security as: "when all people at all times have access to sufficient, safe, nutritious food to maintain a healthy and active life". Food security roughly depends on three factors: 1) availability of food; 2) access to food and 3) appropriate use of food, as well as adequate water and sanitation. The first factor is dependent on growing conditions and weather and climate. In a previous paper we have investigated this factor by evaluating the effect of large scale climate oscillation on land surface phenology (Brown et al., 2010). We found that all areas in Africa are significantly affected by at least one type of large scale climate oscillations and concluded that these somewhat predictable oscillations could perhaps be used to forecast agricultural production. In addition, we have evaluated changes in agricultural land surface phenology over time (Brown et al., 2012). We found that land surface phenology models, which link large-scale vegetation indices with accumulated humidity, could successfully predict agricultural productivity in several countries around the world. In this chapter we are interested in the effect of variability in peak timing of the growing season, or phenology, on the second factor of food security, food access. In this chapter we want to determine if there is a link between market prices and land surface phenology and to determine which markets are vulnerable to land surface phenology changes and variability and which market prices are not correlated.

Prices↗
DOE OSTI2026

Agricultural residue production by county - mature-market medium scenario

This dataset contains data on agricultural residue production by county from 2022 to 2041. The agricultural residue includes barley straw, corn stover, oats straw, sorghum stubble, and wheat straw. The dataset was obtained from the database of the BT23 (Davis et al., 2024) for the mature-market medium scenario with biomass market prices from $50 to $130 per dry ton. For access to this dataset, please use the contact form and indicate the dataset by name.

agricultural residues↗
DOE OSTI2024

Plant Disease Detection Technology Assessment

Visual inspections by US Customs and Border Protection agriculture specialists have identified approximately 20,000 regulated, quarantined pests each year in agricultural products entering the United States. Most of these pests identified in the Agriculture Quarantine and Inspection (AQI) program are insects. Many pathogens are difficult to detect in agricultural products, particularly in early stages of infection. New technologies can help to detect plant pathogens and the diseases that they cause. This technology assessment was performed for the US Department of Homeland Security Science and Technology Directorate (DHS S&T) through the Food, Agriculture, and Veterinary Defense (FAV-D) program to identify emerging technologies that could address this hard problem. These emerging technologies differ in their diagnostic sensitivities and specificities, as well as in their measurement time and training requirements. New instruments that detect volatile organic compounds characteristic of plant disease or pathogens could provide a less invasive inspection method. Dogs, which can successfully detect many concealed agricultural products, have also been trained to detect some plant pests and pathogens. Simple immunological tests offer sensitive and specific detection of many pathogens at the point of use. Advanced imaging methods that use AI to sort fruits and vegetables and recognize anomalies at high speeds could be used in cooperation with exporters to improve food quality and reduce pests. Advances in nucleic acid–based detection methods that have become gold standards for confirmatory diagnostics are now making those methods available for faster, point-of-use detection. These new methods should be developed in the context of AQI operational requirements, which apply risk-based sampling protocols to protect agriculture and facilitate commerce and passenger transit.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A life cycle analysis (LCA) primer for the agricultural community

Consumer demand for sustainably produced agricultural products is increasing. One approach that can be used to evaluate and compare product sustainability is to conduct a life cycle analysis (LCA). The term LCA is broadly used to describe a suite of analytical resources and standardized methods. Life cycle analyses are a transdisciplinary tool which can and are used by all professions but work best when conducted by teams with diverse skills and backgrounds. The objective of this paper is to provide a primer on LCAs for the agricultural community and for LCA practitioners unfamiliar with agronomy. Agricultural LCAs can differ greatly because agricultural products have multiple end uses, complex socio-economic and environmental trade-offs, and can be generated using a variety of different practices, resources, and production systems. Through worldwide agricultural marketing, intricate agronomic supply chains and support systems have been developed to produce, store, and distribute agricultural products. In many situations, the production practices are not linked to the products consumers purchase. This limitation can be partially overcome by conducting an LCA, which is a systematic summation of the multiple environmental impacts associated with the production, use, and disposal of a product. However, the large number and types of analyses can make it difficult for non-practitioners and decision-makers to use and interpret LCA results. Finally, it is important for members of the agricultural community to be aware of these analyses and how they can be used and how they affect product markets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Trade and Climate Mitigation Interactions Create Agro–Economic Opportunities With Social and Environmental Trade–Offs in Latin America and the Caribbean

The Latin America and the Caribbean (LAC) region plays key roles in both meeting global agricultural demands and maintaining carbon sinks due to its abundant land and water resources. In this study we use the Global Change Analysis Model (GCAM) to evaluate the opportunities and challenges posed by two global-scale drivers: agricultural market integration (i.e., reduction of trade barriers) and land-based climate mitigation policy. We evaluate their potential individual and combined impacts on agricultural production and trade revenues across LAC’s economies through mid-century, as well as the resulting impacts on agricultural consumers and integrated land-water-climate systems across the region’s diverse sub-regions. Increased global market integration results in increased agricultural production and trade revenues for many LAC economies driven by their evolving comparative advantages. Climate mitigation measures on CO 2 and non-CO 2 greenhouse gases increase revenues due to increased agricultural prices from land competition and emissions abatement. The combined outcomes from both drivers are complex and sometimes non-linear, highlighting the importance of understanding the interactions between multiple drivers. Our results show that increased agricultural production and trade opportunities pose significant trade-offs that require careful multi-sectoral planning, such as emissions reduction challenges, potential loss of livestock production when pursuing land-based climate mitigation strategies, increased consumer expenditures, and changes in land-use or water withdrawals, resulting in deforestation or water scarcity pressures. There is considerable heterogeneity in economic and environmental outcomes across LAC sub-regions and agricultural commodities, illustrating the value of considering outcomes at finer scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Can Food–Energy–Water Nexus Research Keep Pace with Agricultural Innovation?

The interconnection among food–energy–water (FEW) systems in meeting societal demands is broadly acknowledged. Similarly, competitive or synergistic allocations of water and energy resources for agricultural production, manufacturing, and human consumption are understood, and their economic impacts can be predicted. Far less appreciated and understood are the outcomes of the FEW nexus in response to operation changes in agricultural practices and the associated technological innovations for future generations. Also, the inter-scale and feedback effects of emerging technology-driven resource reallocation and decision-making on FEW systems are largely unknown. For example, how do the agroeconomic feedbacks of intelligent technologies influence the FEW nexus of agricultural production under environmental and demographic changes? How does the necessary water allocation for powering non-powered dams and pumped-storage hydropower generation influence agricultural production and municipal water supply maintenance? How do solar and wind energy farms influence land use for agriculture and the rural economy? In turn, how can the generated solar and wind energy help reduce the cost of groundwater extraction or water desalination?

42 ENGINEERING↗
NASA NTRS2023

Future Climate Change Impacts on U.S. Agricultural Yields, Production, and Market

This study provides estimates of climate change impacts on U.S. agricultural yields and the agricultural economy through the end of the 21st century, utilizing multiple climate scenarios. Results from a process-based crop model project future increases in wheat, grassland, and soybean yield due to climate change and atmospheric CO2 change; corn and sorghum show more muted responses. Results using yields from econometric models show less positive results. Both the econometric and process-based models tend to show more positive yields by the end of the century than several other similar studies. Using the process-based model to provide future yield estimates to an integrated agricultural sector model, the welfare gain is roughly $16B/year (2019 USD) for domestic producers and $6.2B/year for international trade, but domestic consumers lose $10.6B/year, resulting in a total welfare gain of $11.7B/year. When yield projections for major crops are drawn instead from econometric models, total welfare losses of more than $28B/year arise. Simulations using the process-based model as input to the agricultural sector model show large future production increases for soybean, wheat, and sorghum and large price reductions for corn and wheat. The most important factors are those about economic growth, flooding, international trade, and the type of yield model used. Somewhat less, but not insignificant factors include adaptation, livestock productivity, and damages from surface ozone, waterlogging, and pests and diseases.

Agricultural sector↗
DOE OSTI2020

Are scenario projections overly optimistic about future yield progress?

Historical increases in agricultural production were achieved predominantly by large increases in agricultural productivity. Intensification of crop and livestock production also plays a key role in future projections of agricultural land use. Here, we assess and discuss projections of crop yields by global agricultural land-use and integrated assessment models. To evaluate these crop yield projections, we compare them to empirical data on attainable yields by employing a linear and plateauing continuation of observed attainable yield trends. While keeping in mind the uncertainties of attainable yields projections and future climate change impacts, we find that, on average for all cereals on the global level, global projected yields by 2050 remain below the attainable yields. Additionally, this is also true for future pathways with high technological progress and mitigation efforts, indicating that projected yield increases are not overly optimistic, even under systemic transformations. Furthermore, on a regional scale, we find that for developing regions, specifically for sub-Saharan Africa, projected yields stay well below attainable yields, indicating that the large yield gaps which could be closed through improved crop management, may also persist in the future. In OECD countries, in contrast, current yields are already close to attainable yields, and the projections approach or, for some models, even exceed attainable yields by 2050. This observation parallels research suggesting that future progress in attainable yields in developed regions will mainly have to be achieved through new crop varieties or genetic improvements. The models included in this study vary widely in their implementation of yield progress, which are often split into endogenous (crop management) improvements and exogenous (technological) trends. More detail and transparency are needed in these important elements of global yields and land use projections, and this paper discusses possibilities of better aligning agronomic understanding of yield gaps and yield potentials with modelling approaches.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Do agrivoltaics improve public support for solar? A survey on perceptions, preferences, and priorities

Abstract Agrivoltaic systems integrate agricultural production with solar photovoltaic electricity generation. Given the proven technical, economic, and environmental co-benefits provided by agrivoltaic systems, increased proliferation is anticipated, which necessitates accounting for the nuances of community resistance to solar development on farmland and identifying pathways for mitigation. Minimizing siting conflict and addressing agricultural communities’ concerns will be key in continued deployment of agrivoltaics, as localized acceptance of solar is a critical determinant of project success. This survey study assessed if public support for solar development increases when energy and agricultural production are combined in an agrivoltaic system. Results show that 81.8% of respondents would be more likely to support solar development in their community if it integrated agricultural production. This increase in support for solar given the agrivoltaic approach highlights a development strategy that can improve local social acceptance and the deployment rate of solar. Survey respondents prefer agrivoltaic projects that a) are designed to provide economic opportunities for farmers and the local community b) are not located on public property c) do not threaten local interests and d) ensure fair distribution of economic benefits. Proactively identifying what the public perceives as opportunities and concerns related to agrivoltaic development can help improve the design, business model, and siting of systems in the U.S.

Pascaris, Alexis S. (ORCID:0000000253806927)↗
DOE OSTI2022

Lignin-first biorefining of Nordic poplar to produce cellulose fibers could displace cotton production on agricultural lands

Here, we show that lignin-first biorefining of poplar can enable the production of dissolving cellulose pulp that can produce regenerated cellulose, which could substitute cotton. These results in turn indicate that agricultural land dedicated to cotton could be reclaimed for food production by extending poplar plantations to produce textile fibers. Based on climate-adapted poplar clones capable of growth on marginal lands in the Nordic region, we estimate an environmentally sustainable annual biomass production of ~11 tonnes/ha. At scale, lignin-first biorefining of this poplar could annually generate 2.4 tonnes/ha of dissolving pulp for textiles and 1.1 m 3 biofuels. Life cycle assessment indicates that, relative to cotton production, this approach could substantially reduce water consumption and identifies certain areas for further improvement. Overall, this work highlights a new value chain to reduce the environmental footprint of textiles, chemicals, and biofuels while enabling land reclamation and water savings from cotton back to food production.

09 BIOMASS FUELS↗